What I do

MACHINE LEARNING ENTHUSIAST EAGER TO PUSH THE BOUNDARIES OF AI

git
linux
python
sql-database
mongodb
aws
docker
machine-learning
neural-network

Design and implement machine learning models for predictive analysis

Develop robust data processing pipelines and optimize AI algorithms for efficiency

Integration of machine learning models with cloud services like AWS

Create immersive data visualizations and interpret complex data sets to provide actionable insights

Education

Rutgers University–New Brunswick

Master of Science in Data Science

September 2022 - Present

Relevant Coursework:

Natural language processing
Data Mining
Database Management System
Data Wrangling

Indian Institute of Technology Madras

Bachelor of Technology

July 2018 - July 2022

Relevant Coursework:

Introduction to Scientific Computing
Introduction to Data Analytics
Mathematical Foundations of Data Science
Parallel Scientific Computing

Experiences

Senior Python Developer

June 2023 – Current

Risk Mitigation Solutions: Developed and implemented machine learning-based risk mitigation solutions, including abusive account detection and fraud detection, resulting in a significant reduction in incidents and improved platform safety.
Robust Modeling Infrastructure: Enhanced modeling infrastructure by improving labels, features, and algorithms, leading to increased robustness, automation, and generalization. This reduced the modeling and operational load on risk adversaries and new product/risk ramping-ups.
Privacy and Compliance: Contributed to improving risk machine learning excellence by incorporating privacy and compliance considerations, ensuring interpretability, risk perception, and analysis in the models and solutions developed.

Machine Learning Engineer

June 2021 – June 2022

Advanced Machine Learning Techniques: Utilized advanced machine learning techniques such as deep neural networks, transfer learning, and time series analysis to develop models and algorithms for risk prediction and mitigation, resulting in improved accuracy and effectiveness.
Data Processing Efficiency: Optimized data processing pipelines by leveraging technologies like Hadoop, Hive, and Spark, enhancing the efficiency of data cleaning, preprocessing, and feature engineering, leading to faster model development and deployment.
Model Interpretability: Implemented model interpretation techniques to improve the explainability of risk models, enabling a better understanding of model decisions and facilitating risk analysis and mitigation strategies.

Data Analyst

May 2019 – May 2021

Attrition Risk Analysis: Conducted analysis on employee attrition risks using statistical and machine learning techniques, providing valuable insights into potential attrition factors and contributing to the development of targeted retention strategies.
Data Visualization: Created insightful visualizations using tools like Tableau to communicate attrition trends and patterns to stakeholders, enabling data-driven decision-making and proactive talent management strategies.
Strategic HR Initiatives: Collaborated with HR teams to propose and implement strategic initiatives based on data-driven insights, including improvements in benefit policies, safety measures, and inclusion programs, resulting in a positive impact on employee engagement and reduced attrition rates.

Reach Out to me!

Discuss a project or just want to say hi? My Inbox is open for all.

"Machine Learning Engineer | Python, TensorFlow, PyTorch, Keras | Always Learning | Exploring the AI frontier "

New Brunswick, NJ

Open for opportunities: Yes

Hi all, I'm Vivek